Comparative cardiovascular outcomes of novel drugs as an addition to conventional triple therapy for heart failure with reduced ejection fraction (HFrEF): a network meta-analysis of randomised controlled trials.

BACKGROUND: Currently, there is no head-to-head comparison of novel pharmacological treatments for heart failure with reduced ejection fraction (HFrEF). A network meta-analysis aimed to compare effects of both conventional and alternative drug combinations on time to develop primary composite outcome of cardiovascular death or heart failure hospitalisation (PCO). METHODS: Randomised controlled trials (RCTs) were identified from Medline, Scopus up to June 2021. The RCTs were included if comparing any single or combination of drugs, that is, ACE inhibitors (ACEI), angiotensin receptor blockers, beta-blockers (BB), mineralocorticoid receptor antagonists (MRA), ivabradine (IVA), angiotensin receptor blocker/neprilysin inhibitors (ARNI) and sodium-glucose cotransporter-2 inhibitors (SGLT2i), soluble guanylyl cyclase and omecamtiv mecarbil and reporting PCO. Data were extracted from Kaplan-Meier curves, individual patient data were generated. A mixed-effect Weibull regression was applied. Median time to PCO, HRs with 95% CI were estimated accordingly. Our findings suggested that ACEI+BB+MRA+SGLT2i, BB+MRA+ARNI, and ACEI+BB+MRA+IVA had lower probability of PCOs than the conventional triple therapy (ACEI+BB+MRA). RESULTS: Median time to PCOs of ACEI+BB+MRA was 57.7 months whereas median times to those new combinations were longer than 57.7 months. In addition, the three new regimens had a significantly lower PCO risks than ACEI+BB+MRA, with the HRs (95% CI) of 0.51 (0.43 to 0.61), 0.55 (0.46 to 0.65) and 0.56 (0.47 to 0.67), accordingly. CONCLUSION: This study suggested that SGLT2i, ARNI and IVA in addition to ACEI+BB+MRA may be better in prolonging time to develop PCO in HFrEF patients.

Maximal Glycemic Difference, the Possible Strongest Glycemic Variability Parameter to Predict Mortality in ICU Patients.

BACKGROUND: This retrospective study aimed to determine the correlation of blood glucose and glycemic variability with mortality and to identify the strongest glycemic variability parameter for predicting mortality in critically ill patients. METHODS: A total of 528 patients admitted to the medical intensive care unit were included in this study. Blood glucose levels during the first 24 hours of admission were recorded and calculated to determine the glycemic variability. Significant glycemic variability parameters, including the standard deviation, coefficient of variation, maximal blood glucose difference, and J-index, were subsequently compared between intensive care unit survivors and nonsurvivors. A binary logistic regression was performed to identify independent factors associated with mortality. To determine the strongest glycemic variability parameter to predict mortality, the area under the receiver operating characteristic of each glycemic variability parameter was determined, and a pairwise comparison was performed. RESULTS: Among the 528 patients, 17.8% (96/528) were nonsurvivors. Both survivor and nonsurvivor groups were clinically comparable. However, nonsurvivors had significantly higher median APACHE-II scores (23 [21, 27] vs. 18 [14, 22]; p < 0.01) and a higher mechanical ventilator support rate (97.4% vs. 74.9%; p < 0.01). The mean blood glucose level and significant glycemic variability parameters were higher in nonsurvivors than in survivors. The maximal blood glucose difference yielded a similar power to the coefficient of variation (p = 0.21) but was significantly stronger than the standard deviation (p = 0.005) and J-index (p = 0.006). CONCLUSIONS: Glycemic variability was independently associated with intensive care unit mortality. Higher glycemic variability was identified in the nonsurvivor group regardless of preexisting diabetes mellitus. The maximal blood glucose difference and coefficient of variation of the blood glucose were the two strongest parameters for predicting intensive care unit mortality in this study.